Biometric matching system

ABSTRACT

The present disclosure concerns a method of identifying a biometric record of an individual in a database comprising a plurality of biometric records, each record comprising at least one reference biometric sample, the method comprising: receiving, by a biometric identification unit ( 202 ), an input biometric sample with associated source information; selecting, by the biometric identification unit using a reference table ( 210 ), and based on said source information a matching process; and applying by said biometric identification unit said selected matching process to at least some of said biometric records of said database to determine whether said input biometric sample matches a reference biometric sample of one of said biometric records.

The present application is related to co-pending U.S. patentapplications entitled BIOMETRIC MATCHING ENGINE having Attorney DocketNo. 33836.98.0022 and BIOMETRIC TRAINING AND MATCHING ENGINE havingAttorney Docket No. 33836.98.0023, both of which are filed on even dateherewith.

FIELD

The present disclosure relates to identifying a record in a biometricdatabase based on an input biometric sample.

BACKGROUND

The use of biometric data for the identification of individuals isincreasingly becoming the preferred choice in many environments due tothe relative difficulty in fraudulently replicating the data. Forexample, due to increasing fraud involving payment cards such as creditcards, it has been proposed to use biometric data, such as for examplefingerprints, to identify customers in shops or supermarkets to allow apayment transaction to be initiated. As a further example, biometricdata is increasing used for identifying individuals authorized to enterrestricted areas, such as, for example, gyms, apartment blocks orvehicles, or to pass through a border control. Furthermore, criminaldatabases have long been used for identifying individuals based onbiometric data, such as, for example, a fingerprint or facial imagetaken at a crime scene.

To identify individuals, a biometric sample is obtained and compared tothe records of a database, until a match is found. In the majority ofapplications, speed is of the essence. For example, if a user is at thecheckout of a supermarket, or at a border control gate, anidentification delay of more than several seconds may be consideredunacceptable. A further requirement is that there are very few errors,i.e. very few false positive and false negative results. Indeed, if acustomer at the checkout of a supermarket can not be identified, or iswrongly identified, this could lead to the customer being unable to makethe payment, or to the wrong person being billed.

However, there is at least one technical problem in increasing the speedof identification and/or in reducing the error rate in current biometricidentification systems.

SUMMARY

It is an aim of embodiments of the present disclosure to at leastpartially address one or more problems in the prior art.

According to one aspect, there is provided a method of identifying abiometric record of an individual in a database comprising a pluralityof biometric records, each record comprising at least one referencebiometric sample, the method comprising: receiving, by a biometricidentification unit, an input biometric sample with associated sourceinformation; selecting, by the biometric identification unit using areference table, and based on said source information a matchingprocess; and applying by said biometric identification unit saidselected matching process to at least some of said biometric records ofsaid database to determine whether said input biometric sample matches areference biometric sample of one of said biometric records. Forexample, selecting the matching process comprises selecting the matchingprocess to be applied to each of said at least some biometric records ofthe database.

According to one embodiment, selecting said matching process comprisesat least selecting a filtering threshold used for eliminating records ofsaid database.

According to another embodiment, the method further comprises assigningan amount of processing resources to said matching process based on saidsource information, the amount of processing resources determining theprocessing time of said matching process.

According to another embodiment, the method further comprises, prior toapplying said selected matching process, selecting, based on said sourceinformation, records of said database to which said matching process isto be applied.

According to another embodiment, the method further comprises extractinga quality value from said input biometric sample, wherein a filteringthreshold for eliminating records during said selected matching processis selected based on said quality value.

According to another embodiment, selecting the matching processcomprises either: selecting a filtering algorithm used for eliminatingrecords of said database; or selecting a filtering threshold used foreliminating records of said database; or selecting the type of biometricsample used for eliminating records of said database; or selecting theamount of processing resources to be used for eliminating records fromsaid database; or a combination of any of the above.

According to another embodiment, the method further comprises initiatingby said biometric identification unit an electronic payment based on aresult of said matching process.

According to another embodiment, the method further comprises, prior toreceiving said input biometric sample, enrolling said individual byadding a new record containing at least one reference biometric sampleof said individual to said database.

According to another embodiment, the method further comprisesassociating in said database said new record with at least two sourceapparatuses.

According to a further aspect, there is provided a biometricidentification system comprising: a database comprising a plurality ofbiometric records, each record comprising at least one referencebiometric sample; an input for receiving an input biometric sample withassociated source information; and a biometric identification unitconfigured to: select, using a reference table and based on said sourceinformation a matching process; and apply said selected matching processto said biometric records of said database to determine whether saidinput biometric sample matches a reference biometric sample of one ofsaid biometric records.

According to one embodiment, said input is in communication with atleast two remote source apparatuses each comprising a biometriccapturing device.

According to another embodiment, each of said at least two sourceapparatuses is either: a merchant payment terminal; or an entry systemto a restricted area; or a border control gate; or a combination of anyof the above.

According to another embodiment, said biometric identification unit isconfigured to apply said selected matching process to the records ofsaid database that are associated with one of said source apparatuses asindicated by said source information.

According to another embodiment, the system further comprises a lookuptable indicating a link between each record of said database and paymentaccount details.

According to another embodiment, said payment account details includepayment information to enable a payment to be initiated.

The details of various embodiments are set forth in the accompanyingdrawings and the description below. Other potential features will becomeapparent from the description, the drawings and the claims.

BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing and other purposes, features and aspects of the disclosurewill become apparent from the following detailed description of exampleembodiments, given by way of illustration and not limitation withreference to the accompanying drawings, in which:

FIG. 1 schematically illustrates a biometric identification system;

FIG. 2A schematically illustrates a biometric identification systemaccording to an example embodiment;

FIG. 2B schematically illustrates a biometric identification unit ofFIG. 2A in more detail according to an example embodiment;

FIG. 3 illustrates a portion of a biometric database according to anexample embodiment;

FIG. 4 is a flow diagram illustrating operations in a method ofidentifying a biometric record according to an example embodiment;

FIG. 5 schematically illustrates the biometric identification system ofFIG. 2A in more detail according to an example embodiment;

FIG. 6A is a flow diagram showing operations in a method of registeringa new user of a biometric identification system;

FIG. 6B is a flow diagram showing operations in a method of identifyingthe new user during a transaction according to example embodiments;

FIG. 7 is a flow diagram showing operations of a matching processaccording to an example embodiment;

FIGS. 8A and 8B illustrate examples of extracted metadata according toan example embodiment.

Throughout the figures, like features have been labelled with likereference numerals.

DETAILED DESCRIPTION

FIG. 1 illustrates a biometric identification system 100 comprising amatching engine 102 for identifying a record matching an input biometricsample from a single source apparatus 104. As used herein, “sourceapparatus” designates one or more devices that provide biometric samplesand allow access to products, to a restricted area, or to other type ofservices, if an authorized record holder is identified. For example, thesource apparatus 104 could correspond to a cashier terminal in asupermarket, or an entry barrier at an airport lounge.

Matching engine 102 receives a biometric input sample S_(B) from abiometric capturing device (BCD) 106 of the source apparatus 104. Thebiometric capturing device 106 is for example a visible light orinfra-red camera, a fingerprint sensor, microphone or any other detectorsuitable for capturing a biometric sample of an individual. Inputbiometric sample S_(B) could for example be a photo of the face, afingerprint, an iris scan, an image of a signature, a finger vein orpalm vein image, a voice sample, or any other form of biometric data.

In some cases the individual is present at the capturing device 106 andsubmits the biometric input sample, for example by presenting their faceto a camera or placing a finger on a fingerprint detector. In othercases, the biometric data may be retrieved from another source, such asfrom the scene of a crime in the case of a fingerprint, or from asurveillance video image.

Engine 102 has access to a biometric database (DB) 108 storing biometricrecords each associated with one or more reference biometric samples. Abiometric sample is defined herein as data in the form of an imageand/or biometric template based on the image, representing biometricdata of an individual. Engine 102 searches the biometric database for arecord having a reference biometric sample matching the input biometricsample. A result R is provided on an output 110 to receiving equipment112 of the source apparatus 104. The result R for example simplyindicates whether or not a match was found, or may also contain dataassociated with the matching record, such as a reference number of thematching record, the identity, such as name, of the individualassociated with the matching record, or other data. The receivingequipment 112 is for example any equipment that reacts to the result Rof the matching process to provide or deny access to one or moreproducts, restricted areas or services.

The matching engine 102 of the biometric identification system 100 ofFIG. 1 is programmed to apply certain matching processes in order toprovide the result R within a certain time delay and with a desiredaccuracy, in other words with a given percentage of false positive orfalse negative matches. However, the time delay and accuracyrequirements may change, and the accuracy of the matching engine 102 mayevolve in time due for example to a degradation of the biometriccapturing device 106.

FIG. 2A illustrates an alternative biometric identification system 200comprising a biometric identification unit 102 for identifying a recordmatching an input biometric sample from two different source apparatuses204A and 204B, via a communications channel 205. In alternativeembodiments there may be more than two source apparatuses.Communications channel 205 could for example be a wired and/or wirelessconnection comprising a local area network (LAN), a metropolitan datanetwork (MAN), wide area network (WAN) and/or the internet. Thus thebiometric identification unit 202 provides a centralized identificationservice for a plurality of source apparatuses/clients. Such anarrangement may for example be referred to as an “in the cloud”approach.

The source apparatuses 204A, 204B comprise biometric capturing devices206A, 206B respectively, which provide respective input biometricsamples S_(B1) and S_(B2) to the biometric identification unit 202.While each source apparatus 204A, 204B has been illustrated with asingle capturing device 206A, 206B, each may comprise one or moreadditional biometric capturing devices, which for example allow amatching record to be identified based on more than one biometricsample.

The biometric identification unit 202 has access to a common database(CDB) 208, which stores biometric records for both the users registeredto access the products of services offered by source apparatus 204A andthose registered to access the products or services offered by sourceapparatus 204B. As will be explained in more detail below, there may besome overlap, meaning that some users may be registered to use bothapparatuses 204A, 204B.

The biometric identification unit 202 also has access to a referencetable 210, which for example indicates which matching process is to beused for requests originating from each of the source apparatuses 204A,204B, and may also indicate the level of service to be offered, in termsof speed and/or accuracy.

For example, each of the entities associates with the source apparatuses204A, 204B pays for a certain level of service, such that the inputbiometric samples submitted by their respective capturing devices 206A,206B for identification are processed with a certain accuracy and/or ata certain speed. In some cases, the cost may also be based on the numberof records that must be searched, and/or the quality of the biometricsamples provided by the capturing devices 206A, 206B. The quality of asample may be defined in any of a number of ways, such as by thesharpness, contrast or size of an image, as will be described in moredetail below with reference to FIGS. 8A and 8B.

As one example, the source equipment 204A could correspond to a bordercontrol gate that automatically identifies individuals based on a facialimage. As such, it may be desirable that the matching process has veryfew false positive matches, and is performed very quickly on a verylarge number of potentially matching records. The source equipment 204Bis for example a cashier terminal at a point of sale in a shop orsupermarket, allowing customers to use a fingerprint detector toinitiate a payment for their purchases. There may be relatively fewcustomers registered with this payment service, and thus few records mayhave to be searched, and a longer matching delay may be permissible whencompared to the requirements in the border control example. Thus thereference table 210 for example indicates that, for biometric samplesoriginating from source apparatus 204A, a high level of processingresources/priority is to be applied in order to achieve a fast result,and a matching process is to be used that results in very few falsepositives. On the other hand, the reference table may indicate thatrelatively low level of processing resources/priority is to be appliedto records originating from source apparatus 204B, and but that amatching process with very few false positive and false negative resultsis to be applied.

The results R1 and R2 from the matching processes applied to the inputbiometric samples S_(B1) and S_(B2) respectively are provided tocorresponding receiving equipment 212A, 212B of the source apparatus204A, 204B respectively.

The matching process used for identifying a matching biometric record inthe biometric database 208 may comprise one or more matching operations.A matching operation is one that compares an input biometric sample toat least one reference biometric sample of one or more records in thebiometric databases in order to determine a similarity score that isused to identify a matching record.

FIG. 2B illustrates the biometric identification unit 202 of FIG. 2A inmore detail according to one example. As illustrated, the unit 202comprises one or more processors 220 that may operate in parallel underthe control of one or more instruction memories 222. The processors 220may comprise one or more microprocessors, microcontrollers, digitalsignal processors, or appropriate combinations thereof, and executesinstructions stored in the instruction memory or memories 222, whichcould be a volatile memory such as a DRAM (dynamic random accessmemory), or another type of memory.

The processors 220 are also in communication via an interface 223 withone or more memory devices, for example comprising non-volatilememories, such as hard disk drives or FLASH drives (not illustrated inFIG. 2B) that store the common biometric database 208, reference table210, and may also store other databases described in more detail below.

A display 224, as well as one or more input devices 226 such as akeyboard or mouse, may be provided for allowing an administrator tocontrol the operations of the biometric identification unit 202, forexample to download software updates, etc.

A communications interface 228 for example provides a connection to thesource apparatuses 204A, 204B, and in particular to the biometriccapturing devices 206A, 206B and receiving devices 212A, 212B, via thecommunications channel 205 described above.

FIG. 3 illustrates a portion of the common biometric database 208 ofFIG. 2A, storing biometric records according to an example embodiment.Each record of the database corresponds to a different individual. Theparticular record holders of the records stored in the database 208 willdepend on with source apparatus 204A, 204B they are registered with, andcould correspond to members of a gym, customers of a shop orsupermarket, employees of an office, travellers wishing to cross aborder, or other types of record holders.

In FIG. 3, three biometric records are shown as an example, havingreferences “0001”, “0002” and “0003” respectively indicated in a field302. Of course in practise the database is likely to contain hundreds orthousands of records. Each biometric record is associated with acorresponding record holder, but for security reasons, the database 208for example only identifies these individuals by a reference number. Aseparate table, for example stored by the biometric identification unit202, may indicate the mapping between the reference numbers of field 302and biographic information of the corresponding record holder, such asname, address, account details etc., depending on the application.

A field 304 for example comprises a digital image of the face of therecord holder, a field 306 for example comprises a digital image of thefingerprint of the record holder, a field 308 for example comprises adigital image of an iris scan of the record holder, and a field 310 forexample comprises a digital image of the signature of the record holder.Fields 304, 306, 308 and 310 may additionally or alternatively storebiometric templates, generated based on the corresponding images. Ofcourse, in alternative examples of the biometric database 208, only someof these fields may be present and/or addition fields comprising otherbiometric data could be included.

In the example of FIG. 3, not all records comprise a sample in eachfield 304 to 310. For example, some of the record holders may not haveprovided some of the reference samples. In particular, only records 0001and 0002 comprise images of the face of the record holder in field 304,labelled “image1A” and “image 2A” respectively. Furthermore, onlyrecords 0002 and 0003 comprise fingerprint images in field 306, labelled“image2B” and “image3B” respectively, and only records 0001 and 0003comprise iris scan images in field 308, labelled “image1C” and “image3C”respectively. All three records comprise signature images in field 310,labelled “image1D”, “image2D” and “image3D” respectively.

A field 312 for example indicates which source apparatuses the recordholder is registered to use. In the example of FIG. 3, the recordholders of records “0001” and “0003” are registered with sourceapparatuses A and B respectively, which correspond to the sourceapparatuses 204A and 204B in FIG. 2A respectively. The record holder ofrecord “0002” is registered with both source apparatuses A and B.

While in FIG. 3 an example of the common biometric database 208 isillustrated in which a single group of records contains those of recordholders registered with each of the source apparatuses 204A, 204B, inalternative embodiments, the common database 208 could be partitionedsuch that there is a separate portion of the database corresponding toeach source apparatus, and users registered with more than one sourceapparatus appear in each corresponding database partition.

FIG. 4 is a flow diagram illustrating operations in a method ofidentifying a biometric record according to an example embodiment.

In an operation 401, a biometric input sample is received from one ofthe biometric capturing devices 206A, 206B of source apparatuses 204A,204B. The input biometric sample is for example transmitted along withsource information indicating from which of the source apparatuses 204A,204B it originates.

In a subsequent operation 402, the reference table 210 of FIG. 2B isused to identify and select, based on the source information, at leastthe particular matching process to be applied to the input biometricsample. This operation may also involve determining from the referencetable 210 the processing resources to be assigned to this matching task.The processing resources may be inherently defined by the matchingprocess that has been selected, as a function of the particular matchingoperations to be applied. Alternatively or additionally, a prioritylevel and/or a given number of processors is/are assigned to theparticular matching task, based on the source information. For example,the processor block 220 of FIG. 2B comprises multiple processors and oneor more of these processors may be assigned to each matching process.Furthermore, the processor time of the one or more of the processors 220is for example shared between the matching tasks to be performed, andthe higher the priority, the greater the duration of the timeslots thatare allocated to the corresponding task.

In a next operation 403, the selected matching process is applied toidentify, among the records of the common database associated with thesource apparatus, a record having a reference biometric sample matchingthe input biometric sample.

FIG. 5 schematically illustrates the biometric identification system 200of FIG. 2A in more detail according to one particular example.

In FIG. 5, the biometric identification system 200 comprises remoteapparatus 502, an identity services framework module 504, memory banks506, and a payment module 508.

The remote apparatus 502 includes the source apparatus 204A, which inthis example is a merchant payment terminal comprising the biometriccapture device 206A and a cashier terminal application implementing thereceiving equipment 212A. The source apparatus 204B (not illustrated inFIG. 5) is for example of the same type, but corresponds to a differentmerchant. The remote apparatus 502 also comprises a management reportingmodule 509, which for example generates performance statistics, apre-enrolment web portal 510 implementing a customer support interface512, and an enrolment kiosk 514 implementing an enrolment application516.

The identity services framework comprises the reference table 210, aswell as an event logging and reporting database 518, which for examplestores event data used by the management reporting module 509.

The memory banks 506 include a biometric matching module comprising thecommon biometric database 208, storing the biometric samples, forexample in the form of templates. The memory banks 506 also include abiographic database 520, for example storing personal details of recordholders and optionally storing the biometric images, based on which thebiometric templates may be generated. The memory banks 506 also includea service data block 522 comprising a lookup table linking biometricrecords to payment information, as will be described in more detailbelow.

The payment module 508 includes a number of applications supportingvarious payment schemes, in this example direct debit and prepaidpayment schemes. The direct debit payment scheme involves the use of afinancial administration package 524 that controls the execution ofpayment requests. Package 524 for example communicates with a directdebit collection module 526, allowing payments to be debited directlyfrom a user bank account, and also with the collecting bank 528, whichis the bank associated with the source apparatus that is to receive thefunds. The direct connection (pre-paid) payment scheme involves the useof a direct connection collection module 534, that communicates with theacquiring bank 536 receiving the funds and with the issuing bank 538supplying the funds from the account of the user.

Operation of the biometric identification system 200 of FIG. 5 will nowdescribed in more detail with reference to FIGS. 6A and 6B.

FIG. 6A is a flow diagram showing an example of operations performed forregistering a new user to use one or more of the source apparatuses204A, 204B to access products or services.

In a first operation 601, a user enters biographical information andbanking data, for example via an internet webpage using the customersupport interface 512 of the pre-enrolment web portal 510 of FIG. 5. Theuser may also indicate the service or services that he/she wishes to beable to access using one or more biometric samples.

In a next operation 602, the data entered in operation 601 is sent tothe biometric identification unit 202.

In a next operation 603, a record, for example having an identifier“ID123”, is generated in the biographic database 520, and the usersbiographic data is stored in this record.

In a next operation 604, the record identifier “ID123 is sent to thepayment module 508, where the banking data is verified, and acorresponding record is created containing the banking data, for examplehaving the reference “IDABC”.

In a next operation 607, the lookup table 522 is modified to linktogether identifiers “ID123” and “IDABC” as corresponding to a sameuser.

In a next operation 608, the identifier “ID123” of the biographic recordis sent to the user via the pre-enrolment web portal 510.

In a next operation 609, the user is for example invited to presenthimself/herself at the enrolment kiosk 514, where one or more biometriccapturing devices is available. The identifier ID123 is entered, and theuser's identity is for example manually verified based on one or moreidentity documents such as an ID card or passport.

In a next operation 610, one or more biometric reference samples of theuser are captured, and transmitted in a subsequent operation 611 to thebiometric identification unit 202.

In a next operation 612, templates are created and deduplication isperformed. This step for example involves generating, based on thebiometric image or images, templates for use during the subsequentbiometric process. Deduplication then for example involves performing amatching process based on the new templates, and verifying that thereare no high scoring records already in the database, which couldindication that the same person has already been registered.

In a next operation 613, a new record, for example having an identifier“ID741”, is created, and in a subsequent operation 614, the previouslycreated record ID123 is replaced by record ID741, which additionallystores the captured reference biometrics. The lookup table 522 isupdated accordingly. Such a manipulation of identifiers is for exampleperformed to provide improved data privacy between databases of thematching system.

FIG. 6B is a flow diagram showing an example of subsequent operationsfor initiating and executing an identification request for a user, oncethe user has enrolled to use one or more source apparatuses.

In an operation 615, items in a shop or supermarket are scanned and thetotal bill is generated by the cashier terminal application 212A.

In a next operation 616, the customer opts to pay using biometricidentification, and an input biometric sample is captured by thecapturing device 206A.

In a next operation 617, the biometric sample, activity and sourceinformation, and the payment amount are transmitted to the biometricidentification system. The activity information for example indicatesthat a payment is to be made, and the source information for exampleidentifies the source apparatus or merchant.

In a next operation 618, a matching process is selected and performed,as described above with reference to FIG. 4. A matching record, in thisexample the record with identifier “ID741”, is identified.

In a next operation 619, the lookup table 522 is used to identify thebanking record associated with the user, in this example record IDABC.

In a next operation 620, the banking data associated with record IDABCis used to initiate a payment of the corresponding amount from the userto the bank account of the merchant, and in an operation 621 aconfirmation is transmitted to the merchant that the payment has beenauthorised, such that the products can be released.

FIG. 7 is a flow diagram showing examples of operations in a biometricmatching process applied by the biometric identification unit 202 ofFIG. 2A, which is for example implemented by the processing devices ofFIG. 2B.

In an operation 701, the biometric identification unit 202 loads theinput biometric sample and some or all of the reference biometric datasamples ready for comparison. For example, the samples are loaded into amemory device of the biometric identification unit 202.

In a subsequent operation 702, a first filtering operation is used tofilter the records associated with the identified source apparatus. Thisis achieved based on a comparison of the input biometric sample with acorresponding reference sample of each record, to filter out at leastsome of the records. The first filtering operation is for example chosento filter out around 50 percent of the records very quickly and withrelatively few false negatives. The filter is for example associatedwith a threshold that determines the records to be filtered in orfiltered out, based on a similarity score determined for the record. Apermissive threshold, for example relatively low, can be chosen suchthat a relatively high number of records are filtered in. A restrictivethreshold, for example relatively high, can be chosen such that arelatively high number of records are filtered out. Generally, thethreshold is chosen such that, while there may be a high likelihood thata non-matching record is filtered in, there is a very low risk that thematching record is erroneously filtered out during this operation.

As an example, assuming that during the first filtering operation asimilarity score of the input biometric sample with each record isprovided on a scale of 1 to 100, it may be determined that any recordscoring less than 50 can be filtered out as it is very unlikely thatsuch a low-scoring record corresponds to a match. Of course, it may bequite likely that a lot of non-matching records score over such athreshold, but the aim of the first filter is for example to reduce thenumber or records as much as possible.

In a subsequent operation 703, a second filtering operation is used toanalyse the remaining records to identify, if present, the record with amatching biometric sample. The comparison performed in this operationmay or not be based on the same input biometric sample as used in thefirst filtering operation 702. The second filtering operation is forexample chosen to have very low false negative and false positiveresults, and is thus for example slower to execute per record than thefirst filtering operation. For example, this second filtering operationreturns just one or a few of the best matching records. In one example,a similarity score determined in the second filtering operation isprovided on a scale of 1 to 100, and a match is only considered if therecord reaches a score of at least 90, which is for example known to bequite rare in the case of a non-matching record.

In a subsequent operation 704, it is determined whether or not amatching record has been identified. For example, in some embodiments,the second filtering operation 703 only indicates a match if there isrelatively high certainty. In alternative embodiments, the secondfiltering operation 703 always outputs the best matching record, andalso indicates the level of certainty that the record is a match, i.e.that the input biometric data sample came from the record holder. Insuch an embodiment, operation 704 may involve comparing the level ofcertainty with a threshold in order to judge whether there is a match.For example, a match is considered to have occurred if there is at least99 percent certainty. Alternatively, the certainty level of the matchingrecord from each database partition could be used to select the bestmatching record.

After operation 704, if a match was found from the partition beingprocessed, the next operation is 705, in which this result is output. Inparticular, the score of each record is for example compared to athreshold score, and if this threshold is exceeded, the record isconsidered to be a match. If no record is found to have a scoreexceeding the threshold, then there will be no match. If more than onerecord is found to have a score exceeding the threshold, then an alertis for example generated, and a manual verification is performed.

The flow diagram of FIG. 7 provides just one example of a type ofmatching process that could be applied in order to find a record in thedatabase 208 having one or more reference biometric samples matching oneor more input biometric samples. There are various features of thisprocess that can be modified to provide alternative matching processes,such as the particular filtering operations 702 and 703, the thresholdsapplied in the operation 702, and the type of biometric data samplecompared in operations 702, 703, which could be the same or different.Furthermore, rather than the two-phase approach involving the first andsecond filtering operations, alternative matching processes couldinvolve applying only the second filtering operation, or an additionalfiltering operations after the second filtering operation, the finalfiltering operation for example reducing the number of records to justone, or indicating the best matches. The particular matching process tobe applied for an input biometric sample from a given source apparatusis determined by the reference table 210 described above.

The particular techniques used to compare the biometric samples anddetect a match will be known to those skilled in the art, and are forexample based on cascaded tests. For example, fingerprint and facerecognition is discussed in the publication “Intelligent BiometricTechniques in Fingerprint and Face Recognition”, Jain, L.C. et al. and“Partially Parallel Architecture for AdaBoost-Based Detection WithHaar-like Features”, Hiromote et al., the contents of which are herebyincorporated by reference to the extent allowable by the law.

FIGS. 8A and 8B respectively illustrate examples of metadata extractedfrom database records and from biometric input samples, which are forexample used to determine a quality value of either or both of thesamples to be compared. Such a quality value is for used to determine adifficulty score, indicating the difficulty of accurately identifying amatch or non-match for the pair of records.

With reference first to FIG. 8A, a table 800 shows in rows some examplesof metadata that may be extracted from a few of the biometric referencesamples of database portion 300 of FIG. 3. For example, for the photo offace “image1A” of record “0001”, the metadata for example comprises theage and gender of the record holder, in this example having therespective values 66 and male. This information is for example obtainedfrom the record holder.

Furthermore, data relating to the image may be extracted.

For example the image size may be extracted as the number of pixels inthe rectangular image, which in the example of “image1A” is for example1200 by 1600 pixels.

A sharpness level may be evaluated on a scale of 1 to 10 usingtechniques known to those skilled in the art, which in the example of“image1A” is equal to 8.

A viewing angle may be determined, a zero angle for example indicatingthat the face is head-on to the camera, a positive angle indicating aface turned to the right, and a negative angle indicating a face turnedto the left. In the example of “image1A”, the angle is for example 5degrees.

A contrast level, for example on a scale of 1 to 20, may also beevaluated by techniques that will be known to those skilled in the art.In the example of “image1A”, the value is 11.

It will be apparent to those skilled in the art that only some of thesevalues, and/or additional values, could be extracted from the databasesamples. Furthermore, metadata indicating the particular types ofbiometric reference samples present in each record is for exampleextracted.

An overall quality score may be determined for each record, for exampleon a scale of 0 to 10, indicating an overall quality rating of thebiometric sample based on the various parameters available. An exampleof this score is shown in the right-hand column of table 800.

With reference to FIG. 8B, a table 850 shows an example of metadata thatcould be extracted from two input biometric samples “input1A” and“input1B”, which are for example a face image and a fingerprintrespectively. In this example, the extracted metadata is for example theimage size, the image sharpness, the viewing angle and an overallquality score, which are determined using the same criteria as describedabove in relation to FIG. 8A.

The difficulty score is for example evaluated for each input biometricsample, or for each comparison to be performed. As an example, if aninput biometric sample is to be compared to 50 reference biometricsamples of the biometric database, a difficulty score may be determinedfor each of these 50 comparisons based on a quality value of either orboth of the samples that are compared. The quality score may bedetermined based any one or combination of the quality values shown inthe columns of tables 800 and 850 of FIGS. 8A and 8B. In one example, aquality score of a pair of records is evaluated by multiplying theoverall quality score for each record, or by subtracting one of theviewing angles from the other to determine a difference in the viewingangles.

The difficulty scores that have been determined may be used for billingpurposes, and/or to adjust the thresholds used during the matchingprocess such that a target performance can be achieved.

A feature of the example embodiments described herein is that, byselecting a matching process to be applied based on source information,the use of the processing resources of the biometric identificationunit, and thus the processing time, may be optimized for each sourceapparatus.

While a number of specific embodiments of devices and methods of thepresent disclosure have been provided above, it will be apparent tothose skilled in the art that various modifications and alternativescould be applied.

For example, it will be apparent to those skilled in the art that theexamples of matching processes applied to the records are merely a fewsuch examples, and that other matching processes could be used.

Embodiments of the subject matter and the operations described in thisspecification can be implemented in digital electronic circuitry, or incomputer software, firmware, or hardware, including the structuresdisclosed in this specification and their structural equivalents, or incombinations of one or more of them. Embodiments of the subject matterdescribed in this specification can be implemented as one or morecomputer programs, i.e., one or more modules of computer programinstructions, encoded on computer storage medium for execution by, or tocontrol the operation of, data processing apparatus. Alternatively or inaddition, the program instructions can be encoded on anartificially-generated propagated signal, e.g., a machine-generatedelectrical, optical, or electromagnetic signal, which is generated toencode information for transmission to suitable receiver apparatus forexecution by a data processing apparatus. A computer storage medium canbe, or be included in, a computer-readable storage device, acomputer-readable storage substrate, a random or serial access memoryarray or device, or a combination of one or more of them. Moreover,while a computer storage medium is not a propagated signal, a computerstorage medium can be a source or destination of computer programinstructions encoded in an artificially-generated propagated signal. Thecomputer storage medium can also be, or be included in, one or moreseparate physical components or media (e.g., multiple CDs, disks, orother storage devices).

The operations described in this specification can be implemented asoperations performed by a data processing apparatus on data stored onone or more computer-readable storage devices or received from othersources.

The term “data processing apparatus” encompasses all kinds of apparatus,devices, and machines for processing data, including by way of example aprogrammable processor, a computer, a system on a chip, or multipleones, or combinations, of the foregoing The apparatus can includespecial purpose logic circuitry, e.g., an FPGA (field programmable gatearray) or an ASIC (application-specific integrated circuit). Theapparatus can also include, in addition to hardware, code that createsan execution environment for the computer program in question, e.g.,code that constitutes processor firmware, a protocol stack, a databasemanagement system, an operating system, a cross-platform runtimeenvironment, a virtual machine, or a combination of one or more of them.The apparatus and execution environment can realize various differentcomputing model infrastructures, such as web services, distributedcomputing and grid computing infrastructures.

A computer program (also known as a program, software, softwareapplication, script, or code) can be written in any form of programminglanguage, including compiled or interpreted languages, declarative orprocedural languages, and it can be deployed in any form, including as astand-alone program or as a module, component, subroutine, object, orother unit suitable for use in a computing environment. A computerprogram may, but need not, correspond to a file in a file system. Aprogram can be stored in a portion of a file that holds other programsor data (e.g., one or more scripts stored in a markup languagedocument), in a single file dedicated to the program in question, or inmultiple coordinated files (e.g., files that store one or more modules,sub-programs, or portions of code). A computer program can be deployedto be executed on one computer or on multiple computers that are locatedat one site or distributed across multiple sites and interconnected by acommunication network.

The processes and logic flows described in this specification can beperformed by one or more programmable processors executing one or morecomputer programs to perform actions by operating on input data andgenerating output. The processes and logic flows can also be performedby, and apparatus can also be implemented as, special purpose logiccircuitry, e.g., an FPGA (field programmable gate array) or an ASIC(application-specific integrated circuit).

Processors suitable for the execution of a computer program include, byway of example, both general and special purpose microprocessors, andany one or more processors of any kind of digital computer. Generally, aprocessor will receive instructions and data from a read-only memory ora random access memory or both. The essential elements of a computer area processor for performing actions in accordance with instructions andone or more memory devices for storing instructions and data. Generally,a computer will also include, or be operatively coupled to receive datafrom or transfer data to, or both, one or more mass storage devices forstoring data, e.g., magnetic, magneto-optical disks, or optical disks.However, a computer need not have such devices. Moreover, a computer canbe embedded in another device, e.g., a mobile telephone, a personaldigital assistant (PDA), a mobile audio or video player, a game console,a Global Positioning System (GPS) receiver, or a portable storage device(e.g., a universal serial bus (USB) flash drive), to name just a few.Devices suitable for storing computer program instructions and datainclude all forms of non-volatile memory, media and memory devices,including by way of example semiconductor memory devices, e.g., EPROM,EEPROM, and flash memory devices; magnetic disks, e.g., internal harddisks or removable disks; magneto-optical disks; and CD-ROM and DVD-ROMdisks. The processor and the memory can be supplemented by, orincorporated in, special purpose logic circuitry.

To provide for interaction with a user, embodiments of the subjectmatter described in this specification can be implemented on a computerhaving a display device, e.g., a CRT (cathode ray tube) or LCD (liquidcrystal display) monitor, for displaying information to the user and akeyboard and a pointing device, e.g., a mouse or a trackball, by whichthe user can provide input to the computer. Other kinds of devices canbe used to provide for interaction with a user as well; for example,feedback provided to the user can be any form of sensory feedback, e.g.,visual feedback, auditory feedback, or tactile feedback; and input fromthe user can be received in any form, including acoustic, speech, ortactile input. In addition, a computer can interact with a user bysending documents to and receiving documents from a device that is usedby the user; for example, by sending web pages to a web browser on auser's client device in response to requests received from the webbrowser.

Embodiments of the subject matter described in this specification can beimplemented in a computing system that includes a back-end component,e.g., as a data server, or that includes a middleware component, e.g.,an application server, or that includes a front-end component, e.g., aclient computer having a graphical user interface or a Web browserthrough which a user can interact with an implementation of the subjectmatter described in this specification, or any combination of one ormore such back-end, middleware, or front-end components. The componentsof the system can be interconnected by any form or medium of digitaldata communication, e.g., a communication network. Examples ofcommunication networks include a local area network (“LAN”) and a widearea network (“WAN”), an inter-network (e.g., the Internet), andpeer-to-peer networks (e.g., ad hoc peer-to-peer networks).

A system of one or more computers can be configured to performparticular operations or actions by virtue of having software, firmware,hardware, or a combination of them installed on the system that inoperation causes or cause the system to perform the actions. One or morecomputer programs can be configured to perform particular operations oractions by virtue of including instructions that, when executed by dataprocessing apparatus, cause the apparatus to perform the actions.

The computing system can include clients and servers. A client andserver are generally remote from each other and typically interactthrough a communication network. The relationship of client and serverarises by virtue of computer programs running on the respectivecomputers and having a client-server relationship to each other. In someembodiments, a server transmits data (e.g., an HTML page) to a clientdevice (e.g., for purposes of displaying data to and receiving userinput from a user interacting with the client device). Data generated atthe client device (e.g., a result of the user interaction) can bereceived from the client device at the server.

While this specification contains many specific implementation details,these should not be construed as limitations on the scope of anyinventions or of what may be claimed, but rather as descriptions offeatures specific to particular embodiments of particular inventions.Certain features that are described in this specification in the contextof separate embodiments can also be implemented in combination in asingle embodiment. Conversely, various features that are described inthe context of a single embodiment can also be implemented in multipleembodiments separately or in any suitable sub-combination. Moreover,although features may be described above as acting in certaincombinations and even initially claimed as such, one or more featuresfrom a claimed combination can in some cases be excised from thecombination, and the claimed combination may be directed to asub-combination or variation of a sub-combination.

Similarly, while operations are depicted in the drawings in a particularorder, this should not be understood as requiring that such operationsbe performed in the particular order shown or in sequential order, orthat all illustrated operations be performed, to achieve desirableresults. In certain circumstances, multitasking and parallel processingmay be advantageous. Moreover, the separation of various systemcomponents in the embodiments described above should not be understoodas requiring such separation in all embodiments, and it should beunderstood that the described program components and systems cangenerally be integrated together in a single software product orpackaged into multiple software products.

Thus, particular embodiments of the subject matter have been described.Other embodiments are within the scope of the following claims. In somecases, the actions recited in the claims can be performed in a differentorder and still achieve desirable results. In addition, the processesdepicted in the accompanying figures do not necessarily require theparticular order shown, or sequential order, to achieve desirableresults. In certain implementations, multitasking and parallelprocessing may be advantageous.

1. A method of identifying a biometric record of an individual in adatabase (206) comprising a plurality of biometric records, each recordcomprising at least one reference biometric sample, the methodcomprising: receiving, by a biometric identification unit (202), aninput biometric sample with associated source information indicatingsource apparatus (204A, 204B) from which said input biometric sampleoriginates; selecting, by the biometric identification unit using areference table (210), and based on said source information a matchingprocess; and applying by said biometric identification unit saidselected matching process to at least some of said biometric records ofsaid database to determine whether said input biometric sample matches areference biometric sample of one of said biometric records.
 2. Themethod of claim 1, wherein selecting said matching process comprises atleast selecting a filtering threshold used for eliminating records ofsaid database.
 3. The method of claim 1, further comprising assigning anamount of processing resources to said matching process based on saidsource information, the amount of processing resources determining theprocessing time of said matching process.
 4. The method of claim 1,further comprising, prior to applying said selected matching process,selecting, based on said source information, records of said database towhich said matching process is to be applied.
 5. The method of claim 1,further comprising extracting a quality value from said input biometricsample, wherein a filtering threshold for eliminating records duringsaid selected matching process is selected based on said quality value.6. The method of claim 1, wherein selecting said matching processcomprises either: selecting a filtering algorithm used for eliminatingrecords of said database; or selecting a filtering threshold used foreliminating records of said database; or selecting the type of biometricsample used for eliminating records of said database; or selecting theamount of processing resources to be used for eliminating records fromsaid database; or a combination of any of the above.
 7. The method ofclaim 1, further comprising initiating by said biometric identificationunit an electronic payment based on a result of said matching process.8. The method of claim 1, further comprising, prior to receiving saidinput biometric sample, enrolling said individual by adding a new recordcontaining at least one reference biometric sample of said individual tosaid database.
 9. The method of claim 8, further comprising associatingin said database said new record with at least two source apparatuses.10. A biometric identification system comprising: a database (208)comprising a plurality of biometric records, each record comprising atleast one reference biometric sample; an input for receiving an inputbiometric sample with associated source information indicating sourceapparatus (204A, 204B) from which said input biometric sampleoriginates; and a biometric identification unit (202) configured to:select, using a reference table (210) and based on said sourceinformation a matching process; and apply said selected matching processto said biometric records of said database to determine whether saidinput biometric sample matches a reference biometric sample of one ofsaid biometric records.
 11. The biometric identification system of claim10, wherein said input is in communication with at least two remotesource apparatuses (204A, 204B) each comprising a biometric capturingdevice (206A, 206B).
 12. The biometric identification system of claim11, wherein each of said at least two source apparatuses is either: amerchant payment terminal; or an entry system to a restricted area; or aborder control gate; or a combination of any of the above.
 13. Thebiometric identification system of claim 11, wherein said biometricidentification unit is configured to apply said selected matchingprocess to the records of said database that are associated with one ofsaid source apparatuses as indicated by said source information.
 14. Thesystem of claim 10, further comprising a lookup table (522) indicating alink between each record of said database and payment account details.15. The system of claim 14, wherein said payment account details includepayment information to enable a payment to be initiated.